In this project, we are going to solve some problems with the help of machine learining. The very first problem is to guess the OS of a mobile and the other is to guess the price of it. Our predictions are based on the hardware configuration of mobile phones. The main purpose in this repository is to learn about some machine learining algorithms and how to use them in scikit-learn package.
The data provided in this project has been gathered from GSMArena website. The date that we have fetched this data was about feburary of 2024.
Our evaluation metric for OS prediction is F1-score. Our final result for this problem is about 96 percent.
As this is a simple project for learning to work with scikit-learn and numpy and pandas, maybe there will be better results for predictions, using some other libraries. But we tried to create our models only with this three libraries and nothing else.
As you can see, our project has been written in python. You need to have python 3.9 at least. also our code has been written in jupyter notebooks. So, you need an interpretor for reading jupyter files.
Beside what we have descussed on the last paragraph, you only need to install numpy, pandas, seaborn, matplotlib and scikit-learn with pip and that's it!
pip install pandas numpy scikit-learn
pip install matplotlib==3.7.1
pip install seaborn==0.12.2
As there is a lot of changes in functions of matplotlib and seaborn, if you want to use our codes with no problems and bugs, it is prefered to use the version that we have used for writing this project. Otherwise, you may face some problems in running codes.
That's it! enjoy this simple toturial for Data Science and Machine Learning.
Thank you for your attention.